It is well known that manual evaluation of biological samples is both slow and highly susceptible to error. It is also well known that automating the sample evaluation both increases the sample evaluation rate and reduces error.
FIG. 1 is a schematic of an automated scanning optical microscopy system. The automated scanning optical microscopy system 100 includes an optical microscope modified to automatically capture and save images of a sample 105 placed on a sample holder 107 such as, for example, a slide, which in turn is supported by a stage 110. The optical components include an illumination source 120, objective lens 124, and camera 128. Housing 130 supports the optical components. The design and selection of the optical components and housing are known to one of skill in the optical art and do not require further description.
The automated system 100 includes a controller that enables the stage 110 supporting the slide 107 to place a portion of the sample 105 in the focal plane of the objective lens. The camera 128 captures an image of the sample and sends the image signal to an image processor for further processing and/or storage. In the example, shown in FIG. 1, the image processor and controller are both housed in a single PC 104 although other variations may be used. The mechanical design of the stage 110 is known to one of skill in the mechanical arts and does not require further description.
The controller may also control a sample handling subsystem 160 that automatically transfers a slide 109 between the stage 110 and a storage unit 162.
The controller must also be capable of positioning the sample such that the image produced by the camera 128 is in focus. In addition, the controller must be able to position the sample very rapidly in order to reduce the time required to capture an image.
One method of auto-focusing an image employs a laser range finder. The controller calculates the distance to a surface based on the signal from the laser range finder. The advantage of such a system is that it is very fast, thereby increasing the scan rate of the automated system. The disadvantage of such a system is that it requires additional hardware that may interfere with the optical performance of the automated system. A second disadvantage of such a system is the inability to focus directly on the feature of interest in the sample. The signal from the laser range finder is usually based on the highest reflective surface encountered by the laser beam. This surface is usually the cover slip or the slide and not the sample.
Another method of auto-focusing an image employs image processing to determine when the image is in focus or, alternatively, select the most focused image from a set of images taken at different sample-objective lens distances. The advantage of using image processing to auto-focus is that it can focus directly on the sample instead of the slide or cover slip. The disadvantage of image processing auto-focus is that it usually requires large computational resources that may limit the scan rate of the automated system. The large computational requirement arises because prior art algorithms based on maximizing the high frequency power spectrum of the image or on detecting and maximizing edges must perform large numbers of computations.
Therefore, there remains a need for a rapid auto-focusing method that does not require large computational resources and can directly focus the sample.